



import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


_snake_case						=    pytest.mark.integration



@require_faiss
class     UpperCAmelCase_       (			_A):







							def   snake_case__ (  self):

														'''simple docstring'''

														_lowerCAmelCase	:				Dict					  =       Dataset.from_dict({"filename": ["my_name-train" + "_" + str(a_) for x in np.arange(30).tolist()]})
														return dset







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Dataset					  =       self._create_dummy_dataset()
														_lowerCAmelCase	:				Optional[int]					  =       dset.map(
														    lambda __a,     __a: {"vecs": i * np.ones(5,     dtype=np.floataa)},     with_indices=a_,     keep_in_memory=a_)
														_lowerCAmelCase	:				List[str]					  =       dset.add_faiss_index("vecs",     batch_size=100,     metric_type=faiss.METRIC_INNER_PRODUCT)
														_lowerCAmelCase	:				str					  =       dset.get_nearest_examples("vecs",     np.ones(5,     dtype=np.floataa))
														self.assertEqual(examples["filename"][0],     "my_name-train_29")
														dset.drop_index("vecs")







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Dataset					  =       self._create_dummy_dataset()
														dset.add_faiss_index_from_external_arrays(
														    external_arrays=np.ones((30, 5)) * np.arange(30).reshape(-1,     1),     index_name="vecs",     batch_size=100,     metric_type=faiss.METRIC_INNER_PRODUCT,     )
														_lowerCAmelCase	:				Tuple					  =       dset.get_nearest_examples("vecs",     np.ones(5,     dtype=np.floataa))
														self.assertEqual(examples["filename"][0],     "my_name-train_29")







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Dataset					  =       self._create_dummy_dataset()
														dset.add_faiss_index_from_external_arrays(
														    external_arrays=np.ones((30, 5)) * np.arange(30).reshape(-1,     1),     index_name="vecs",     metric_type=faiss.METRIC_INNER_PRODUCT,     )

														# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
														# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
														# see https://bugs.python.org/issue14243 and
														# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
														with tempfile.NamedTemporaryFile(delete=a_) as tmp_file:
																					dset.save_faiss_index("vecs",     tmp_file.name)
																					dset.load_faiss_index("vecs2",     tmp_file.name)
														os.unlink(tmp_file.name)

														_lowerCAmelCase	:				Dict					  =       dset.get_nearest_examples("vecs2",     np.ones(5,     dtype=np.floataa))
														self.assertEqual(examples["filename"][0],     "my_name-train_29")







							def   snake_case__ (  self):

														'''simple docstring'''

														_lowerCAmelCase	:				Dataset					  =       self._create_dummy_dataset()
														dset.add_faiss_index_from_external_arrays(
														    external_arrays=np.ones((30, 5)) * np.arange(30).reshape(-1,     1),     index_name="vecs")
														dset.drop_index("vecs")
														self.assertRaises(a_,     partial(dset.get_nearest_examples,     "vecs2",     np.ones(5,     dtype=np.floataa)))







							def   snake_case__ (  self):

														'''simple docstring'''

														from elasticsearch import Elasticsearch

														_lowerCAmelCase	:				Dataset					  =       self._create_dummy_dataset()
														with patch("elasticsearch.Elasticsearch.search") as mocked_search, patch(
														    "elasticsearch.client.IndicesClient.create") as mocked_index_create, patch("elasticsearch.helpers.streaming_bulk") as mocked_bulk:
																					_lowerCAmelCase	:				Tuple					  =       {"acknowledged": True}
																					mocked_bulk.return_value([(True, None)] * 30)
																					_lowerCAmelCase	:				Optional[int]					  =       {"hits": {"hits": [{"_score": 1, "_id": 29}]}}
																					_lowerCAmelCase	:				Optional[int]					  =       Elasticsearch()

																					dset.add_elasticsearch_index("filename",     es_client=a_)
																					_lowerCAmelCase	:				List[str]					  =       dset.get_nearest_examples("filename",     "my_name-train_29")
																					self.assertEqual(examples["filename"][0],     "my_name-train_29")



@require_faiss
class     UpperCAmelCase_       (			_A):







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Dict					  =       FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT)

														# add vectors
														index.add_vectors(np.eye(5,     dtype=np.floataa))
														self.assertIsNotNone(index.faiss_index)
														self.assertEqual(index.faiss_index.ntotal,     5)
														index.add_vectors(np.zeros((5, 5),     dtype=np.floataa))
														self.assertEqual(index.faiss_index.ntotal,     10)

														# single query
														_lowerCAmelCase	:				Tuple					  =       np.zeros(5,     dtype=np.floataa)
														_lowerCAmelCase	:				Dict					  =       1
														_lowerCAmelCase	:				List[str]					  =       index.search(a_)
														self.assertRaises(a_,     index.search,     query.reshape(-1,     1))
														self.assertGreater(scores[0],     0)
														self.assertEqual(indices[0],     1)

														# batched queries
														_lowerCAmelCase	:				Union[str, Any]					  =       np.eye(5,     dtype=np.floataa)[::-1]
														_lowerCAmelCase	:				Optional[int]					  =       index.search_batch(a_)
														self.assertRaises(a_,     index.search_batch,     queries[0])
														_lowerCAmelCase	:				List[Any]					  =       [scores[0] for scores in total_scores]
														_lowerCAmelCase	:				str					  =       [indices[0] for indices in total_indices]
														self.assertGreater(np.min(a_),     0)
														self.assertListEqual([4, 3, 2, 1, 0],     a_)







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Optional[int]					  =       FaissIndex(string_factory="Flat")
														index.add_vectors(np.eye(5,     dtype=np.floataa))
														self.assertIsInstance(index.faiss_index,     faiss.IndexFlat)
														_lowerCAmelCase	:				Tuple					  =       FaissIndex(string_factory="LSH")
														index.add_vectors(np.eye(5,     dtype=np.floataa))
														self.assertIsInstance(index.faiss_index,     faiss.IndexLSH)
														with self.assertRaises(a_):
																					_lowerCAmelCase	:				Tuple					  =       FaissIndex(string_factory="Flat",     custom_index=faiss.IndexFlat(5))







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				Optional[Any]					  =       faiss.IndexFlat(5)
														_lowerCAmelCase	:				Optional[int]					  =       FaissIndex(custom_index=a_)
														index.add_vectors(np.eye(5,     dtype=np.floataa))
														self.assertIsInstance(index.faiss_index,     faiss.IndexFlat)







							def   snake_case__ (  self):

														'''simple docstring'''

														import faiss

														_lowerCAmelCase	:				str					  =       FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT)
														index.add_vectors(np.eye(5,     dtype=np.floataa))

														# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
														# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
														# see https://bugs.python.org/issue14243 and
														# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
														with tempfile.NamedTemporaryFile(delete=a_) as tmp_file:
																					index.save(tmp_file.name)
																					_lowerCAmelCase	:				int					  =       FaissIndex.load(tmp_file.name)
														os.unlink(tmp_file.name)

														_lowerCAmelCase	:				Any					  =       np.zeros(5,     dtype=np.floataa)
														_lowerCAmelCase	:				Tuple					  =       1
														_lowerCAmelCase	:				Dict					  =       index.search(a_)
														self.assertGreater(scores[0],     0)
														self.assertEqual(indices[0],     1)






@require_faiss
def 							A							(   _lowerCamelCase    ):





							'''simple docstring'''




							import faiss

							_lowerCAmelCase	:				Any					  =       FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT    )
							index.add_vectors(np.eye(5							,					dtype=np.floataa    )    )

							_lowerCAmelCase	:				Tuple					  =       "index.faiss"
							_lowerCAmelCase	:				Optional[int]					  =       F"mock://{index_name}"
							index.save(a_							,					storage_options=mockfs.storage_options    )
							_lowerCAmelCase	:				List[Any]					  =       FaissIndex.load(a_							,					storage_options=mockfs.storage_options    )

							_lowerCAmelCase	:				Optional[Any]					  =       np.zeros(5							,					dtype=np.floataa    )
							_lowerCAmelCase	:				Dict					  =       1
							_lowerCAmelCase	:				Optional[int]					  =       index.search(a_    )
							assert scores[0] > 0
							assert indices[0] == 1



@require_elasticsearch
class     UpperCAmelCase_       (			_A):







							def   snake_case__ (  self):

														'''simple docstring'''

														from elasticsearch import Elasticsearch

														with patch("elasticsearch.Elasticsearch.search") as mocked_search, patch(
														    "elasticsearch.client.IndicesClient.create") as mocked_index_create, patch("elasticsearch.helpers.streaming_bulk") as mocked_bulk:
																					_lowerCAmelCase	:				Union[str, Any]					  =       Elasticsearch()
																					_lowerCAmelCase	:				Optional[int]					  =       {"acknowledged": True}
																					_lowerCAmelCase	:				Tuple					  =       ElasticSearchIndex(es_client=a_)
																					mocked_bulk.return_value([(True, None)] * 3)
																					index.add_documents(["foo", "bar", "foobar"])

																					# single query
																					_lowerCAmelCase	:				Dict					  =       "foo"
																					_lowerCAmelCase	:				List[str]					  =       {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
																					_lowerCAmelCase	:				Tuple					  =       index.search(a_)
																					self.assertEqual(scores[0],     1)
																					self.assertEqual(indices[0],     0)

																					# single query with timeout
																					_lowerCAmelCase	:				Union[str, Any]					  =       "foo"
																					_lowerCAmelCase	:				int					  =       {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
																					_lowerCAmelCase	:				Dict					  =       index.search(a_,     request_timeout=30)
																					self.assertEqual(scores[0],     1)
																					self.assertEqual(indices[0],     0)

																					# batched queries
																					_lowerCAmelCase	:				Optional[Any]					  =       ["foo", "bar", "foobar"]
																					_lowerCAmelCase	:				Union[str, Any]					  =       {"hits": {"hits": [{"_score": 1, "_id": 1}]}}
																					_lowerCAmelCase	:				List[str]					  =       index.search_batch(a_)
																					_lowerCAmelCase	:				Any					  =       [scores[0] for scores in total_scores]
																					_lowerCAmelCase	:				Tuple					  =       [indices[0] for indices in total_indices]
																					self.assertGreater(np.min(a_),     0)
																					self.assertListEqual([1, 1, 1],     a_)

																					# batched queries with timeout
																					_lowerCAmelCase	:				Dict					  =       ["foo", "bar", "foobar"]
																					_lowerCAmelCase	:				Optional[Any]					  =       {"hits": {"hits": [{"_score": 1, "_id": 1}]}}
																					_lowerCAmelCase	:				int					  =       index.search_batch(a_,     request_timeout=30)
																					_lowerCAmelCase	:				int					  =       [scores[0] for scores in total_scores]
																					_lowerCAmelCase	:				List[Any]					  =       [indices[0] for indices in total_indices]
																					self.assertGreater(np.min(a_),     0)
																					self.assertListEqual([1, 1, 1],     a_)







'''simple docstring'''






from __future__ import annotations

lowerCAmelCase									=   list[tuple[int, int]]

lowerCAmelCase									=   [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

lowerCAmelCase									=   ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right
class 		lowerCamelCase	:



	def __init__( self		,   a_		,   a_		,   a_		,   a_		,   a_		,   a_		,   ):
			lowerCAmelCase  :     int       						= pos_x
			lowerCAmelCase  :     Union[str, Any]       						= pos_y
			lowerCAmelCase  :     Optional[Any]       						= (pos_y, pos_x)
			lowerCAmelCase  :     Union[str, Any]       						= goal_x
			lowerCAmelCase  :     Tuple       						= goal_y
			lowerCAmelCase  :     str       						= g_cost
			lowerCAmelCase  :     Dict       						= parent
			lowerCAmelCase  :     List[Any]       						= self.calculate_heuristic()



	def 	_lowerCamelCase     ( self						):
			lowerCAmelCase  :     int       						= abs(self.pos_x - self.goal_x						)
			lowerCAmelCase  :     Any       						= abs(self.pos_y - self.goal_y						)
			return dx + dy





	def __lt__( self		,   a_						):
			return self.f_cost < other.f_cost






class 		lowerCamelCase	:



	def __init__( self		,   a_		,   a_						):
			lowerCAmelCase  :     Union[str, Any]       						= Node(start[1]		,   start[0]		,   goal[1]		,   goal[0]		,   0		,   a_						)
			lowerCAmelCase  :     Union[str, Any]       						= Node(goal[1]		,   goal[0]		,   goal[1]		,   goal[0]		,   99_999		,   a_						)

			lowerCAmelCase  :     Tuple       						= [self.start]
			lowerCAmelCase  :     list[Node]       						= []

			lowerCAmelCase  :     Tuple       						= False



	def 	_lowerCamelCase     ( self						):
			while self.open_nodes:
					# Open Nodes are sorted using __lt__
					self.open_nodes.sort()
					lowerCAmelCase  :     List[Any]       						= self.open_nodes.pop(0						)

					if current_node.pos == self.target.pos:
							lowerCAmelCase  :     Tuple       						= True
							return self.retrace_path(a_						)

					self.closed_nodes.append(a_						)
					lowerCAmelCase  :     Tuple       						= self.get_successors(a_						)

					for child_node in successors:
							if child_node in self.closed_nodes:
									continue

							if child_node not in self.open_nodes:
									self.open_nodes.append(a_						)
							else:
									# retrieve the best current path
									lowerCAmelCase  :     int       						= self.open_nodes.pop(self.open_nodes.index(a_						)						)

									if child_node.g_cost < better_node.g_cost:
											self.open_nodes.append(a_						)
									else:
											self.open_nodes.append(a_						)

			if not self.reached:
					return [self.start.pos]
			return None



	def 	_lowerCamelCase     ( self		,   a_						):
			lowerCAmelCase  :     Union[str, Any]       						= []
			for action in delta:
					lowerCAmelCase  :     Dict       						= parent.pos_x + action[1]
					lowerCAmelCase  :     str       						= parent.pos_y + action[0]

					if not (0 <= pos_x <= len(grid[0]						) - 1 and 0 <= pos_y <= len(a_						) - 1):
							continue

					if grid[pos_y][pos_x] != 0:
							continue

					successors.append(
					    Node(
					        a_		,   a_		,   self.target.pos_y		,   self.target.pos_x		,   parent.g_cost + 1		,   a_		,   )						)
			return successors





	def 	_lowerCamelCase     ( self		,   a_						):
			lowerCAmelCase  :     Union[str, Any]       						= node
			lowerCAmelCase  :     List[str]       						= []
			while current_node is not None:
					path.append((current_node.pos_y, current_node.pos_x)						)
					lowerCAmelCase  :     Dict       						= current_node.parent
			path.reverse()
			return path


if __name__ == "__main__":
					lowerCAmelCase									=   (0, 0)
					lowerCAmelCase									=   (len(grid) - 1, len(grid[0]) - 1)
					for elem in grid:
										print(elem)

					print("""------""")

					lowerCAmelCase									=   GreedyBestFirst(init, goal)
					lowerCAmelCase									=   greedy_bf.search()
					if path:
										for pos_x, pos_y in path:
															lowerCAmelCase									=   2

										for elem in grid:
															print(elem)



